Production of industrial engines and off-highway equipment usually involves the assembly of multiple flexible systems, such as hydraulic hoses and wiring harnesses. Assembly faults may cause malfunctions or inefficiencies of the product. Assembly faults may include, for example, missing fasteners and hoses, misrouting of hoses or wires, rubbing of hoses, wires or belts, wrong dimension of hoses or belts, etc. In order to ensure that the systems and parts are correctly assembled, inspection of the product during the assembly process is needed. Assembly inspections are conventionally performed manually by experienced inspectors. During the manual inspection, inspectors usually compare the assembled product with a design chart and detect an assembly fault when there is a difference between the two.
However, manual inspection may be inaccurate and may lead to uncertainties of the defect inspection process. The assembled products may visually vary among each other, and directly matching them with their design charts may lead to mistakes during the visual inspection process. For example, flexible assemblies such as hydraulic hoses may be present in a different orientation or shape as those in the design chart. In addition, manual inspection requires skilled, human labor and can be time-consuming. Therefore, it is desirable to automate the inspection process of machine assemblies.
Several automated inspection systems have been developed that utilize digital image processing techniques to perform assembly inspections. An example of such an automated inspection system is disclosed in U.S. Patent Publication No. 2005/0147287 to Sakai et al. (“the '287 publication”). In particular, the '287 publication discloses a pattern defect inspection method and apparatus that reveal defects on an inspection target. The pattern defect inspection apparatus compares images of corresponding areas of two formed patterns that should be identical with each other, and identifies a defect if any mismatches occur between the images. In particular, the image comparison process may be performed on a plurality of areas simultaneously. Further, the pattern defect inspection apparatus also converts the gradation of the image signals of compared images in each of a plurality of different processes, so that images with the same patterns but different brightness may be properly compared.
Although the method and apparatus of the '287 publication may alleviate some of the problems of manual assembly inspections, it may still be problematic. First, the process may still be inaccurate. A product may include a plurality of assemblies. While it is important that each assembly is correctly assembled, the relative position of the plurality of assemblies may vary from one product to another. The inspection apparatus disclosed by the '287 publication uses the overall pattern of the image, instead of image regions of individual components, and relies on the global matching between images. Therefore, a defect may be incorrectly detected because a relative position between a flexible assembly and other components may be different from that dictated in a design chart. For example, the wirings of the circuit disclosed by the '287 publication may be correct, but the relative location or orientation of the flexible wires may be distinctive from the pattern in the design chart. Such a circuit may be incorrectly determined as faulty by the '287 publication. In addition, because objects in the image are not extracted and identified, the '287 publication may not facilitate identification of specific component assembly faults and provide an informative diagnosis report, besides detecting the existence of such a fault.
The system and method of the present disclosure is directed towards overcoming one or more of the constraints set forth above.